Monitoring of chronobiological rhythms for disease and drug management using one or more implantable device

ABSTRACT

The health state of a subject is automatically evaluated or predicted using at least one implantable device. In varying examples, the health state is determined by sensing or receiving information about at least one physiological process having a circadian rhythm whose presence, absence, or baseline change is associated with impending disease, and comparing such rhythm to baseline circadian rhythm prediction criteria. Other chronobiological rhythms beside circadian may also be used. The baseline prediction criteria may be derived using one or more past physiological process observation of the subject or population of subjects in a non-disease health state. The prediction processing may be performed by the at least one implantable device or by an external device in communication with the implantable device. Systems and methods for invoking a therapy in response to the health state, such as to prevent or minimize the consequences of predicted impending heart failure, are also discussed.

TECHNICAL FIELD

This patent document pertains generally to medical systems and methods.More particularly, but not by way of limitation, this patent documentpertains to monitoring of chronobiological rhythms, such as circadianrhythms, for disease and drug management using one or more implantabledevice.

BACKGROUND

Heart failure (“HF”) is a condition in which a subject's heart can'tpump the needed amount of blood to the subject's other organs causingfluid to build up behind the heart. HF is one of the leading causes ofdeath in the United States and a leading cause of poor quality of lifein the human population over the age of 65. There are currently about 5million or more cases of HF in the United States alone, with about 1million of them hospitalized each year. As the population of subjects 65years of age and older grows (i.e., amid the aging of the baby boomergeneration), HF threatens a dramatic increase of morbidity andmortality, along with being a burgeoning drain on healthcare funds inthe United States and other countries.

Some of many needs for HF subjects is accurately predicting, monitoring,and treating heart failure decompensation before an advanced diseasestage is reached. Heart failure, and more particularly heart failuredecompensation, may signify the drawing near of death or, at the veryleast, the need for extensive hospitalization intervention. Withsufficient warning, steps including drug or electrical stimulus therapycan be initiated or adjusted to save the HF subjects from either ofthese advanced HF consequences. Unfortunately, the time associated withtypical HF detection is often too late in the disease process to preventsignificant clinical intervention (e.g., hospitalization) or death.

OVERVIEW

The health state of a subject is automatically evaluated or predictedusing at least one implantable device. In varying examples, the healthstate is determined by sensing or receiving information about at leastone physiological process having a circadian rhythm whose presence,absence, or baseline change is associated with impending disease, andcomparing such rhythm to baseline circadian rhythm prediction criteria.Other chronobiological rhythms beside circadian may also be used. Thebaseline prediction criteria may be derived using one or more pastphysiological process observation of the subject or population ofsubjects in a non-disease health state. The prediction processing may beperformed by the at least one implantable device or by an externaldevice in communication with the implantable device. Systems and methodsfor invoking a therapy in response to the health state, such as toprevent or minimize the consequences of predicted impending heartfailure, are also discussed.

In Example 1, a system comprises a prediction criteria module, adaptedto store information about one or more chronobiological rhythmprediction criteria; a physiological information collection device,adapted to sense or receive information about at least one physiologicalprocess having a chronobiological rhythm whose presence, absence, orchange is statistically associated with a disease state; an impendingdisease state prediction module, coupled to the prediction criteriamodule to receive the one or more chronobiological rhythm predictioncriteria and coupled to the physiological information collection deviceto receive the chronobiological rhythm of the at least one physiologicalprocess, the impending disease state prediction module being adapted topredict an occurrence of impending disease using the one or morechronobiological rhythm prediction criteria and the chronobiologicalrhythm of the at least one physiological process; and at least one ofthe prediction criteria module, the physiological information collectiondevice, or the impending disease state prediction module including animplantable portion.

In Example 2, the system of Example 1 is optionally configured such thatthe impending disease state prediction module is adapted to predict theoccurrence of impending disease during a specified prediction timeperiod.

In Example 3, the system of Examples 1-2 is optionally configured suchthat the information about the at least one physiological process issensed or received, at least in part, using an implantable device orsensor.

In Example 4, the system of Examples 1-3 is optionally configured suchthat the at least one physiological process includes one or more of bodytemperature, heart rate, heart rate variability, respiration rate,respiration rate variability, minute ventilation, tidal volume,activity, blood pressure, posture, sleep pattern, thoracic impedance, orat least one heart sound.

In Example 5, the system of Example 4 optionally includes a timingcircuit coupled to the physiological information collection device toprovide an associated collection time to the chronobiological rhythm ofthe at least one physiological process; and wherein the associatedcollection time is used by the impending disease state prediction moduleto predict the occurrence of impending disease.

In Example 6, the system of Examples 1-5 optionally includes anarrhythmia detector adapted to sense or receive information about anarrhythmia incidence; and wherein a time of the arrhythmia incidence isused by the impending disease state prediction module to predict theoccurrence of impending disease.

In Example 7, the system of Examples 1-6 is optionally configured suchthat the predicted occurrence of impending disease is computed using oneor more stored weighting factor, each weighting factor corresponding toa chronobiological rhythm of a different one of the at least onephysiological process.

In Example 8, the system of Examples 1-7 is optionally configured suchthat the chronobiological rhythm prediction criteria are derived usingone or more past physiological process observation from a subject in anon-disease state.

In Example 9, the system of Examples 1-8 optionally includes a therapycontrol module adapted to adjust or initiate a therapy using thepredicted occurrence of impending disease.

In Example 10, the system of Example 9 optionally includes animplantable drug pump, coupled to the therapy control module to receiveone or more drug delivery instruction.

In Example 11, the system of Example 9 optionally includes a neuralstimulation circuit, coupled to the therapy control module to receiveone or more neurostimulation delivery instruction.

In Example 12, the system of Example 9 optionally includes at least oneof a ventricular or atrial stimulation circuit, coupled to the therapycontrol module to receive one or more cardiac stimulation deliveryinstruction.

In Example 13, a method comprises sensing or receiving at an implantabledevice, information about at least one physiological process having achronobiological rhythm whose presence, absence, or change isstatistically associated with a disease; comparing the chronobiologicalrhythm of the at least one physiological process to one or morechronobiological rhythm prediction criteria; and at least one ofpredicting, detecting, or identifying an occurrence of disease using thecomparison.

In Example 14, the method of Example 13 is optionally configured suchthat predicting the occurrence of disease includes predicting anoccurrence of impending disease occurring during a specified predictiontime period.

In Example 15, the method of Examples 13-14 is optionally configuredsuch that sensing or receiving the information about the at least onephysiological process includes sensing or receiving at least one of bodytemperature, heart rate, heart rate variability, respiration rate,respiration rate variability, minute ventilation, tidal volume,activity, blood pressure, posture, sleep pattern, thoracic impedance, orat least one heart sound.

In Example 16, the method of Examples 13-15 optionally includes sensingor receiving information about at least one arrhythmia incidence; andwherein predicting the occurrence of disease includes using a time ofday of the arrhythmia incidence.

In Example 17, the method of Examples 13-16 optionally includesadjusting or initiating a therapy using the predicted, detected, oridentified occurrence of disease.

In Example 18, the method of Example 17 is optionally configured suchthat adjusting or initiating the therapy includes determining a drugdelivery time using the chronobiological rhythm of the at least onephysiological process.

In Example 19, the method of Example 17 is optionally configured suchthat adjusting or initiating the therapy includes recovering thechronobiological rhythm of the at least one physiological process usingone or both of drug delivery or neurostimulation.

In Example 20, the method of Example 17 optionally includes monitoringthe efficacy of the therapy using a post-therapy chronobiological rhythmof the at least one physiological process.

In Example 21, a method comprises sensing or receiving at an implantabledevice, information about at least one physiological process having achronobiological rhythm whose presence, absence, or change isstatistically associated with a disease; comparing the chronobiologicalrhythm of the at least one physiological process to one or morechronobiological rhythm prediction criteria; and applying a therapy.

In Example 22, the method of Example 21 is optionally configured suchthat applying the therapy includes using the comparison of thechronobiological rhythm and the one or more chronobiological rhythmprediction criteria.

In Example 23, the method of Examples 21-22 is optionally configuredsuch that applying the therapy includes using a subject-responsive drugdelivery time derived using one or more past post-therapychronobiological rhythm observations from a subject in a similarpre-therapy disease-state.

In Example 24, the method of Examples 21-23 optionally includesmonitoring the efficacy of the therapy using a post-therapychronobiological rhythm of the at least one physiological process.

In Example 25, a method comprises applying a therapy to a subject; andmonitoring the efficacy of the therapy, including sensing or receivingat an implantable device a post-therapy chronobiological rhythmassociated with at least one of body temperature, heart rate, heart ratevariability, respiration rate, respiration rate variability, minuteventilation, tidal volume, activity, blood pressure, posture, sleeppattern, thoracic impedance, or at least one heart sound.

In Example 26, the method of Example 25 is optionally configured suchthat applying the therapy includes delivering one or both of drug orelectrical stimulation therapy to the subject.

In Example 27, the method of Examples 25-26 optionally includestitrating the therapy using the monitored efficacy of the therapy.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, which are not necessarily drawn to scale, like numeralsdescribe substantially similar components throughout the several views.The drawings illustrate generally, by way of example, but not by way oflimitation, various embodiments discussed in the present document.

FIG. 1 is a schematic view illustrating a system adapted to predict,monitor, or treat an occurrence of impending heart failure or otherdisease state in a subject.

FIG. 2 is a block diagram illustrating one conceptual example of asystem adapted to predict, monitor, or treat an occurrence of impendingheart failure or other disease state in a subject.

FIG. 3 is a block diagram illustrating one conceptual example of arhythm collection module.

FIG. 4 is a block diagram illustrating one conceptual example of animpending disease state prediction module.

FIG. 5 is a block diagram illustrating one conceptual example of atherapy control module.

FIG. 6 is a block diagram illustrating exemplary physiological processeshaving circadian rhythms that may be used to predict, monitor, or treatan occurrence of impending heart failure or other disease state in asubject.

FIGS. 7A-7C are graphical illustrations that may be used by a subject orcaregiver to predict, monitor, or treat an occurrence of impending heartfailure or other disease state in the subject.

FIG. 8 illustrates a method of predicting, monitoring, or treating anoccurrence of impending heart failure or other disease state in asubject.

DETAILED DESCRIPTION

The following detailed description includes references to theaccompanying drawings, which form a part of the detailed description.The drawings show, by way of illustration, specific embodiments in whichthe present systems and methods may be practiced. These embodiments,which are also referred to herein as “examples,” are described in enoughdetail to enable those skilled in the art to practice the presentsystems and methods. The embodiments may be combined, other embodimentsmay be utilized or structural, electrical, or logical changes may bemade without departing from the scope of the present systems andmethods. The following detailed description is, therefore, not to betaken in a limiting sense, and the scope of the present systems andmethods are defined by the appended claims and their legal equivalents.

In this document, the terms “a” or “an” are used to include one or morethan one; the term “or” is used to refer to a nonexclusive “or” unlessotherwise indicated; the term “subject” is used to include the term“patient”; and the terms “predict,” “prediction,” or other variantsthereof are used to denote a probability assertion or statementregarding whether or not an occurrence of impending heart failure orother disease state might occur during a specified time period. Inaddition, it is to be understood that the phraseology or terminologyemployed herein, and not otherwise defined, is for the purpose ofdescription only and not of limitation.

Furthermore, all patents and patent documents referred to in thisdocument are incorporated by reference herein in their entirety, asthough individually incorporated by reference. In the event ofinconsistent usages between this document and those documents soincorporated by reference, the usage in the incorporated referencesshould be considered supplementary to that of this document; forirreconcilable inconsistencies, the usage in this document controls.

Introduction

HF and other disease states are associated with a loss or baselinechange of one or more circadian rhythms, especially when the subjectdecompensates. A subject's body, when relatively healthy (i.e., in anon-disease state), has more than 100 circadian rhythms. Each circadianrhythm is a unique, roughly 24-hour cycle of a subject's physiologicalprocess, such as body temperature (core or peripheral), heart rate,heart rate variability, respiration rate, respiration rate variability,minute ventilation, activity, blood pressure, posture, tidal volume,sleep quality or duration, thoracic impedance, or heart sounds, amongothers.

The present systems and methods may predict, monitor, or treat animpending disease state of a subject, such as the likelihood of anoccurrence of heart failure, using circadian or other rhythm monitoring.In certain examples, treating the impending disease state of the subjectincludes adjusting or initiating one or more therapies (e.g., drugtherapy or neurostimulation), such as to prevent, decrease, or minimizesuch predicted impending disease state or monitor the efficacy of suchapplied therapy. In certain examples, monitoring the impending diseasestate of the subject includes monitoring the subject's recovery from theimpending disease state in light of the applied therapy.

As will be discussed below, the prediction, monitoring, or treatment ofan impending disease state can be made by sensing or receiving one ormore circadian (or other chronobiological) rhythms associated with asubject's physiological process and by comparing such rhythm(s) to oneor more baseline chronobiological rhythm prediction criteria that arederived by a caregiver (e.g., a physician) or from at least one subjectin a non-disease state. Advantageously, prediction, monitoring, ortreatment of an impending disease state, such as heart failure, mayreduce or eliminate the need for hospital intervention, and may beuseful for avoiding a decompensation crisis and properly managing aheart failure subject in a state of relative well-being.

EXAMPLES

The techniques of the present systems and methods may be used inapplications involving implantable medical devices (“IMDs”) including,but not limited to, implantable cardiac rhythm management (“CRM”)systems such as pacemakers, cardioverters/defibrillators,pacemakers/defibrillators, biventricular or other multi-siteresynchronization or coordination devices such as cardiacresynchronization therapy (“CRT”) devices, patient monitoring systems,neural modulation systems, and drug delivery systems. In addition, thesystems and methods described herein may also be employed in unimplanteddevices, including but not limited to, external pacemakers, neutralstimulators, cardioverters/defibrillators, pacer/defibrillators,biventricular or other multi-site resynchronization or coordinationdevices, monitors, programmers and recorders, whether such devices areused for providing sensing, receiving, prediction processing, ortherapy.

FIG. 1 is a schematic view illustrating one example of a system 100adapted to predict, monitor, or treat an occurrence of impending heartfailure or other disease state in a subject 110 using sensed or receivedinformation about at least one physiological process having a circadianrhythm whose presence, absence, or baseline change is statisticallyassociated with a disease state, and an environment in which the system100 may be used. As shown in FIG. 1, the system 100 may include an IMD102, such as a CRM device, which can be coupled by at least one lead 108to a heart 106 or efferent parasympathetic nerve, such as a vagus nerve107, of the subject 110. The IMD 102 may be implanted subcutaneously inthe subject's chest, abdomen, or elsewhere. Each of the at least onelead 108 extends from a lead proximal portion 114 to a lead distalportion 112.

The exemplary system 100 also includes a physiological informationcollection device 104, remote portions (e.g., a nearby externaluser-interface 120 or a distant external user interface 122) of whichare shown in FIG. 1, a drug delivery system (e.g., a drug pump 116), anda warning device 118. The remote portions 120, 122 of the physiologicalinformation collection device 104 may provide wireless communicationwith the IMD 102 and with one another using telemetry 150 or other knowncommunication techniques. In one example, the prediction, monitoring, ortreatment of the occurrence of impending heart failure or other diseasestate is made, at least in part, by receiving information about at leastone physiological process having a circadian rhythm remotely (e.g., atthe nearby 120 or distant 122 external user interface) and thencommunicating signals representative of the circadian rhythm, or lackthereof, to the IMD 102 for processing. In certain examples, the remoteportions of the physiological information collection device 104 includea visual or other display 124, such as a LCD or LED display, fortextually or graphically relaying information to the subject 110 or acaregiver regarding operation, findings (e.g., loss or baseline changeof one or more circadian rhythms; recovery of the one or more circadianrhythms), or predictions of the system 100.

The drug pump 116 or another drug dispensing device may be provided inaddition to the IMD 102 to control the delivering of one or more therapydrug to the subject 110 or, if already doing so, to adjust or terminatea dosage of the delivered drug(s). The efficacy of the drug therapy maybe evaluated based on changes, if any, in the circadian rhythms of theat least one physiological process sensed or received by thephysiological information collection device 104. For instance, if thesystem 100 initially detects a loss or baseline change of one or more ofa subject's circadian rhythms (e.g., relative to one or more baselinecircadian rhythm prediction criteria) and thereafter directs the drugpump 116 to deliver a diuretic or other drug in an attempt to regainnormal (or non-disease like) circadian rhythm(s), the efficacy of suchdiuretic drug therapy and the subject's 110 recovery state may beevaluated by monitoring post-therapy circadian rhythm(s) of at least onephysiological process. In a similar manner, the efficacy of electricalstimulation therapy, such as neurostimulation therapy, may be evaluated.

If the system 100, based on circadian rhythm monitoring, comes to theconclusion that an occurrence of heart failure (for example) is likelyto occur during a predicted future time period for the subject 110, oneor more warning signals may be made to the subject or his/her caregiver.Warning signals may be generated using either an internal warning device118 or the external user interfaces 120, 122 so-as-to notify the subject110 or his/her caregiver of the onset of heart failure or other diseasestate. The internal warning device 118 may be a vibrating or audibledevice that provides perceptible stimulation to the subject 110 to alerthim/her of any significant progression of heart failure so that he/shemay immediately consult their caregiver. The external user interfaces120, 122 may provide audible alarm signals to alert the subject 110 aswell textual or graphic displays. In addition, once impending heartfailure has been predicted by the system 100, information used to makethe prediction (e.g., loss of one or more circadian rhythms) is storedwithin the IMD 102 or sent to the distant external user interface 122for review by the caregiver. If warranted, the caregiver may theninitiate or modify a (stimulation or drug) therapy or adjust controlparameters of the IMD 102 or drug pump 116.

FIG. 2 provides a simplified block diagram illustrating one conceptualexample of a system 100 adapted to predict, monitor, or treat anoccurrence of impending heart failure or other disease state in asubject 110 (FIG. 1). In certain examples, treating the impending HF orother disease state includes adjusting or initiating one or moretherapies, such as electrical stimulation or drug therapy. In certainexamples, monitoring the impending HF or other disease state includesmonitoring the subject's 110 recovery from the impending disease inlight of the applied therapy.

FIG. 2 further illustrates an exemplary placement of a plurality ofleads 108A, 108B, 108C, specifically lead distal end portions, within,on, or near a heart 106 of the subject 110. As shown, the heart 106includes (among other things) a right atrium 200A, a left atrium 200B, aright ventricle 202A, and a left ventricle 202B. In this example, anatrial lead 108A includes electrodes disposed in, around, or near theright atrium 200A of the heart 106, such as a ring electrode 204 and atip electrode 206, for sensing signals (e.g., via atrial sensing circuit250) or delivering pacing or other stimulation therapy (e.g., via atrialstimulation circuit 252) to the right atrium 200A. The atrial lead 108Amay also include additional electrodes, such as for delivering atrial orventricular cardioversion/defibrillation or pacing therapy to the heart106.

In FIG. 2, a right ventricular lead 108B is also shown and includes oneor more electrodes, such as a tip electrode 208 and a ring electrode210, for sensing signals (e.g., via ventricular sensing circuit 254) ordelivering pacing or other stimulation therapy (e.g., via ventricularstimulation circuit 256). The right ventricular lead 108B may alsoinclude additional electrodes, such as one or more coil electrode 212Aor 212B for delivering atrial or ventricularcardioversion/defibrillation or pacing therapy to the heart 106.Further, the system 100 of FIG. 2 also includes a left ventricular lead108C, which provides one or more electrodes such as a tip electrode 214and a ring electrode 216, for sensing signals or delivering pacing orother stimulation therapy. The left ventricular lead 108C may alsoinclude one or more additional electrodes, such as coil electrodes 218Aor 218B for delivering atrial or ventricularcardioversion/defibrillation or pacing therapy to the heart 106.

As shown, the IMD 102 includes electronic circuitry components that areenclosed in a hermetically-sealed enclosure, such as a can 220.Additional electrodes may be located on or near an efferentparasympathetic or afferent nerve, on the can 220, on an insulatingheader 222, or on other portions of the IMD 102, such as for sensing orfor providing neurostimulation, pacing, or defibrillation energy, forexample, with or without the electrodes disposed within, on, or near theheart 106. Other forms of electrodes include meshes and patches that maybe applied to portions of the heart 106 or that may be implanted inother areas of the body to help direct electrical currents produced bythe IMD 102. For example, a warning electrode 118 on the insulatingheader 222 may be used to stimulate local muscle tissue to provide analert/warning of a prediction of impending disease to the subject 110.The present systems and methods are adapted to work in a variety ofelectrode configurations and with a variety of electrical contacts orelectrodes in addition to the electrode configuration shown in FIG. 2.

It is to be noted that FIG. 2 illustrates just one conceptualization ofvarious modules, circuits, and interfaces of system 100, which areimplemented either in hardware or as one or more sequences of stepscarried out on a microprocessor or other controller. Such modules,devices, and interfaces are illustrated separately for conceptualclarity; however, it is to be understood that the various modules,devices, and interfaces of FIG. 2 need not be separately embodied, butmay be combined or otherwise implemented. The IMD 102, in particular,may be powered by a power source 230, such as a battery, which providesoperating power to all the IMD internal modules and circuits shown inFIG. 2. In certain examples, the power source 230 should be capable ofoperating at low current drains for long periods of time and also becapable of providing high-current pulses (for capacitor charging) whenthe subject 110 (FIG. 1) requires a shock pulse.

In this example, the system 100 further includes a physiologicalinformation collection device 104 adapted to sense or receiveinformation about at least one physiological process having a circadianrhythm whose presence, absence, or baseline change is statisticallyassociated with a disease state. In varying examples, the at least onephysiological process includes one or more of body temperature (core orperipheral), heart rate, heart rate variability, respiration rate,respiration rate variability, minute ventilation, activity, bloodpressure, posture, tidal volume, sleep quality or duration, thoracicimpedance, or heart sounds. Circadian rhythm representative signalsassociated with the at least one physiological process may be output toa programmable controller 224 for performing the prediction, monitoring,or treatment of the occurrence of impending heart failure or otherdisease state. Additionally or alternatively, a time of the circadianrhythm representative signal collection, a clinical event, or anarrhythmia incidence (atrial or ventricular) may be output to theprogrammable controller 224 and used in the prediction, monitoring, ortreatment. For instance, it has been found that certain diseases, suchas pulmonary edema, tend to disrupt (i.e., lose or change from baseline)at least one physiological process's circadian rhythm at certain timesof a day or week. Using such information, one (e.g., a caregiver or theIMD 102 itself) can more easily treat the impending disease.

As shown, the physiological information collection device 104 mayinclude an atrial sensing circuit 250, a ventricular sensing circuit254, a first information sensor module 226, a second information sensormodule 228, a communication module 232, a (nearby) external userinterface 120 (e.g., a home station device), an external communicationrepeater 236, an Internet or other communication network connection 238,a computerized medical data storage 240, or a (distant) external userinterface 122 (e.g., a physician station device).

The atrial 250 and ventricular 254 sensing circuits, the firstinformation sensor module 226, and the communication module 232 may bedirectly coupled to the programmable controller 224; while the secondinformation sensor module 228, the (nearby) external user interface 120,and the external communication repeater 236 may be communicativelycoupled with the communication module 232 via telemetry, and thus alsobe in communication with the programmable controller 224. In thisexample, the communication module 232 is capable of wirelesslycommunicating with the computerized medical data storage 240 or the(distant) external user interface 122, such as by using the externalcommunication repeater 236 and the Internet/phone connection 238. In oneexample, the nearby 120 or distant 122 external user interface controls,loads, or retrieves information from the IMD 102, and is adapted toprocess and display (e.g., textually or graphically) such informationobtained.

The atrial 250 and ventricular 254 sensing circuits may be selectivelycoupled to the atrial lead 108A, the right ventricular lead 108B, or theleft ventricular lead 108C, via an electrode configuration switchingcircuit 244, for detecting the presence of intrinsic cardiac activity ineach of the four chambers of the heart 106. These intrinsic heartactivity signals typically include depolarizations that propagatethrough the circulatory system. The depolarizations cause heartcontractions for pumping blood through the circulatory system. Theatrial 250 and ventricular 254 sensing circuits may include dedicatedsense amplifiers, multiplexed amplifiers, shared amplifiers, or othersignal processing circuits to extract depolarizations or other usefulinformation from the intrinsic heart activity signals. For instance,each of the atrial 250 or ventricular 254 sensing circuits may employone or more low power, precision amplifier with programmable orautomatic gain, bandpass filtering, or a threshold detection circuit, toselectively sense the cardiac signal of interest.

For arrhythmia detection 246, the IMD 102 utilizes the atrial 250 andventricular 254 sensing circuits to sense cardiac signals fordetermining whether a rhythm is normal or pathologic.

For thoracic impedance detection, the IMD 102 may inject an electricalstimulus current of known or attainable value (e.g., via the ventricular256 or atrial 252 stimulation circuits) to one or more implantedelectrodes and measure (e.g., via the ventricular 254 or atrial 250sense circuits) the resulting voltage using one or more other implantedelectrodes. Using information about the current and the resultingvoltage, the IMD 102 may calculate an impedance by taking a ratio ofresulting voltage to injected current. This measurement may be repeatedover time to detect changes in impedance (and thus changes in fluidamount in the lungs). A reduction in thoracic impedance indicates thepresence of an increase in fluid within the lungs. Conversely, a fluiddecrease in the lungs corresponds to an increase in thoracic impedancesensed.

In FIG. 2, the first 226 and second 228 information sensor modulesinclude one or more physiologic process sensors, such as a temperaturesensor 260, a blood pressure sensor 258, a respiratory rate/respiratoryrate variability sensor 262, a tidal volume/MV sensor 264, an activitysensor 270, a heart rate/heart rate variability sensor 266, a posturesensor 268, or an accelerometer or microphone 267. In one example, eachinformation sensor module 226, 228 also includes one or more interfacecircuits that receive one or more control signals and preprocesses thesensor signal(s) received. In another example, the first 226 and second228 information sensor modules are combined as a single module.

A sleep detector 272 shown associated with the programmable controller224 inputs signals from the various physiological information sensors258-270 or the nearby external user interface 120 to determine whetherthe subject 110 is in a state of sleep, and if so, determines thequality of such sleep. In some examples, the programmable controller 224determines whether the subject 110 is attempting to fall asleep based onwhether the subject is or is not in a recumbent position, determinablevia the posture sensor 268. In some examples, a sleep state detectionsystem, such as described in Dalal et al., U.S. patent application Ser.No. 11/458,602 entitled, “SLEEP STATE DETECTION,” which is assigned toCardiac Pacemakers, Inc., is used to determine whether or not thesubject 110 is in a state of sleep.

Other ways in which the programmable controller 224 may identify whenthe subject 110 (FIG. 1) is attempting to sleep are as follows. In oneexample, the programmable controller 224 may identify the time that thesubject 110 begins attempting to fall asleep based on an indicationreceived from the subject, such as via nearby external user interface120 and the communication module 232. In another example, theprogrammable controller 224 identifies the time the subject 110 beginsattempting to fall asleep based on the activity level of the subjectdetermined via the activity sensor 270. The activity sensor 270 mayinclude one or more accelerometers, gyros, or bonded piezoelectriccrystals that generate a signal as a function of subject activitypattern, such as body motion, foot strikes or other impact events, andthe like. Additionally or alternatively, the activity sensor 270 mayinclude one or more electrodes that generate an electromyogram (“EMG”)signal as a function of muscle electrical activity, which may indicatethe activity level of the subject 110. The electrodes may, for example,be located in the legs, abdomen, cheek, back, or buttocks of the subject110 to detect muscle activity associated with walking, running, or thelike.

The programmable controller 224 includes various functional modules,circuits, and detectors, one conceptualization of which is illustratedin FIG. 2. Among other things, the programmable controller 224 mayinclude control circuitry, a RAM or ROM memory 274, logic and timingcircuitry 277 to keep track of the timing of sensing or receivingcircadian rhythm representative signals associated with physiologicalprocesses of the subject 110 (FIG. 1), for example, and I/O circuitry.Additionally, the programmable controller 224 may include a rhythmcollection module 276 that receives from the physiological informationcollection device 104 information about the at least one physiologicalprocess having a circadian rhythm whose presence, absence, or baselinechange is associated with a disease state. The rhythm collection module276 may include the memory 274 to store signals representative of suchcircadian rhythm(s) and may further classify such rhythm(s) as beingassociated with one or more of body temperature (core or peripheral),heart rate, heart rate variability, respiration rate, respiration ratevariability, minute ventilation, activity, blood pressure, posture,tidal volume, sleep quality or duration, thoracic impedance, or heartsounds.

In this example, the programmable controller 224 also includes aprediction criteria module 278 adapted to store one or more baselinecircadian rhythm prediction criteria. In one example, the one or morebaseline circadian rhythm prediction criteria are derived using one ormore past physiological process observation of the subject when in anon-disease health state (i.e., in a relatively healthy state). Inanother example, the one or more baseline circadian rhythm predictioncriteria are derived using one or more past physiological processobservation of a population when in a non-disease health state. In afurther example, the one or more baseline circadian rhythm predictioncriteria are loaded into the IMD 102 before, during, or after the IMD102 is implanted in the subject 110, such as via an externaluser-interface 120, 122.

For predicting, monitoring, or treating the occurrence of impendingheart failure or other disease state, the programmable controller 224includes an impending disease state prediction module 280 and a therapycontrol module 282. The impending disease state prediction module 280 iscoupled to both the prediction criteria module 278 to receive the one ormore baseline circadian rhythm prediction criteria, and is coupled tothe physiological information collection device 104 (via the rhythmcollection module 276) to receive the circadian rhythm representativesignals associated with the at least one physiological process. Theimpending disease state prediction module 280 predicts the likelihood offuture heart failure, for example, using the one or more baselinecircadian rhythm prediction criteria and the circadian rhythmrepresentative signals associated with the at least one physiologicalprocess sensed or received. More specifically, the impending diseasestate prediction module 280 predicts the likelihood of impending heartfailure based on a determination of whether or not the circadianrhythm(s) of the at least one physiological process have been lost orchanged (e.g., relative to the baseline circadian rhythm predictioncriteria).

The therapy control module 282 is programmed to select (from a set ofavailable therapies) the most appropriate responsive therapy (orcombination of therapies), such as for reducing the likelihood or evenpreventing the predicted occurrence of impending disease (e.g., heartfailure). In one example, the therapy control module 282 also triggersthe delivery of the selected therapy after determining if theprobability of the occurrence of impending disease state, computed bythe impending disease state prediction module 280, warrants suchadministration.

In one example, such therapy is provided via electrodes associated withthe heart 106 or portions of a subject's nervous system such as, forexample, sympathetic or parasympathetic members of the autonomic nervoussystem. In one such example, the electrodes provide neurostimulation viaa neural stimulation circuit 257 in electrical contact with the vagusnerve 107 (FIG. 1) or a baroreceptor, thereby adjusting autonomic toneto restore tone indicative of normal circadian rhythm. The vagus nerve107 provides parasympathetic stimulation to the heart 106 (FIG. 1) thatcounteracts the effects of increased sympathetic activity, andstimulation of the vagus nerve 107 at either a pre-ganglionic orpost-ganglionic site produces dilation of the coronary arteries and areduced workload on the heart 106. Baroreceptors are sensory nerveendings located in the heart 106 and vasculature that are stimulated byincreased fluid pressure. Stimulation of baroreceptors causes impulsesto be relayed via afferent pathways to nuclei in the brainstem thatresult in parasympathetic activation and sympathetic inhibition.

A subject's 110 autonomic balance may vary in accordance with circadianrhythms. To this end, the neural stimulation circuit 257 (via thetherapy control module 282) may be programmed to schedule delivery ofneurostimulation in accordance with the subject's circadian rhythms forincreased beneficial effect. The neural stimulation circuit 257 (via thetherapy control module 282) may be programmed to titrate the delivery ofneurostimulation by scheduling such delivery or adjusting the level ofthe neurostimulation in an open- or closed-loop manner that takes intoconsideration the effects of the circadian rhythm representative signalssensed or received.

In another example, such therapy is provided elsewhere (e.g.,communicated to nearby external user interface 120 or delivered via adrug pump 116 (FIG. 1)) and includes, for example, a drug dose, a dietregimen, or a fluid intake regimen. In either case, the programmablecontroller 224 may control the therapy provided in view of any detectedrecovery or further loss or change of the subject's circadian rhythms.For instance, the programmable controller 224 may direct that therapy beincreased if the subject's circadian rhythms are being further lostrelative to the baseline prediction criteria or that the therapy bedecreased or terminated if the subject's circadian rhythms are beingrecovered (i.e., regained). Further yet, the programmable controller 224may be used to determine the efficacy of any drug or other therapyadministered to the subject 110, such as via drug pump 116.

Moreover, the programmable controller 224, specifically the therapycontrol module 282, can use knowledge of the subject's 110 (FIG. 1)circadian rhythms to determine (1) the time when the subject needs atherapy the most or (2) the time when the subject is most responsive tothe therapy (i.e., a subject-responsive drug delivery time), and thendeliver the therapy as such. For instance, in a preclinical study, itwas found that thoracic impedance followed a pattern of lowevening/night time impedance (indicative of more fluid in the subject)followed by an increasing day time-afternoon impedance (indicative ofless fluid in the subject). Thus, when a specimen was given diureticsduring the day, a greater effect was observed than when diuretics weregiven during the late evening. Consequently, such information can beused to direct the consumption of diuretics or other drugs during theday due to its greater observed effect. Alternatively or additionally,this knowledge may be used to determine an expected drug effect give thetime of day it is administered.

Nearby 120 and distant 122 external user-interfaces may be used in,among other things, programming the IMD 102. Briefly, theuser-interfaces permit a caregiver or other user to program theoperation of the IMD 102 or to retrieve and display information (e.g.,textually or graphically) received from the IMD 102. Depending upon thespecific programming of the external user-interfaces 120, 122, eachinterface may also be capable of processing and analyzing data receivedfrom the IMD 102 and, for example, render an impending disease stateprediction.

FIG. 3 is a block diagram illustrating one conceptual example of aportion of a rhythm collection module 276. In one example, the rhythmcollection module 276 includes a classification module 302 and adetection processing module 304. In such an example, the rhythmcollection module 276 is programmed to recurrently receive, store, anddetect the presence, time (via timing circuitry 277), and magnitude ofthe circadian rhythm representative signals associated with at least onephysiological process sensed or received by the atrial sensing circuit250, the ventricular sensing circuit 254, the first information sensormodule 226, or the communication module 232 (communicatively coupled tothe second information module 228, the (nearby) external user interface120, and the external communication repeater 236). The classificationmodule 302 separates the received circadian rhythm representativesignals into one or more associated physiological process categories,such as body temperature (core or peripheral), heart rate, heart ratevariability, respiration rate, respiration rate variability, minuteventilation, activity, blood pressure, posture, tidal volume, sleepquality or duration, thoracic impedance, or heart sounds. The classifiedcircadian rhythm representative signals are then output to the detectionprocessing module 304, which is adapted to detect the presence, time, ormagnitude of the signals received. From the rhythm collection device276, the circadian rhythm representative signals are output to animpending disease state prediction module 280.

FIG. 4 is a block diagram illustrating one conceptual example of aportion of an impending disease state prediction module 280. In oneexample, the impending disease state prediction module 280 includes aprobability processing module 402 and a prediction processing module404. The impending disease state prediction module 280 includes an inputthat receives the at least one circadian rhythm representative signal(S₁, S₂, . . . , S_(N)) from the rhythm collection module 276 andincludes an input that receives the baseline circadian rhythm predictioncriteria from the prediction criteria module 278. Optionally, theimpending disease state prediction module 280 includes an input thatreceives from an arrhythmia detector 246 or an external user-interface120, 122 a time of day of an arrhythmia incident or a clinical event.

In one example, the probability processing module 402 includes aweighting module 406 and a probability comparator 408. After enteringthe impending disease state prediction module 280, the at least onecircadian rhythm representative signal (S₁, S₂, . . . , S_(N)) and thebaseline circadian rhythm prediction criteria are received by theprobability processing module 402. The probability comparator 408compares one or more circadian rhythm representative signal (S₁, S₂, . .. , S_(N)) value to one or more corresponding baseline circadian rhythmprediction criteria (C₁, C₂, . . . , C_(N)) value, such as one or morevalue sensed at a similar time of day and associated with the samephysiological process. In another example, the at least one circadianrhythm representative signal (S₁, S₂, . . . , S_(N)) is analyzed withrespect to at least one other circadian rhythm representative signalassociated with the same physiological process.

Data analysis and comparison of sensed or received circadian rhythms mayinvolve both graphical and numerical procedures, and may further becharacterized by one or more of a mean/median level, an amplitude, aphase, a period, a wave form, or robustness, for example. For instance,data analysis and comparison techniques that may be used in theprediction of an occurrence of impending disease include, among others,spectral analysis such as a strength or width of the circadian peak ofthe rhythm spectrum, 24-hour synchronous averaging, day/nightdifferences, daily minimum/maximum differences, order statistics such asupper-quartile vs. lower quartile differences, phase lag/drift/stabilitywith respect to a 24-hour clock, or wake/sleep differences.

In one example, for each circadian rhythm representative signal (S₁, S₂,. . . , S_(N)) value or set of chronological circadian rhythm valuesdiffering by more than a specified amount from the baseline predictioncriteria (C₁, C₂, . . . , C_(N)) value or set of values, indicating aloss of circadian rhythm, the probability comparator 408 summarizes(e.g., via logistic regression) and outputs to the prediction processingmodule 404 a probability indication of the occurrence of impendingdisease, such as heart failure. The comparisons may be discrete orcontinuous.

In another example, the weighting module 406 stores weighting factors(Weight₁, Weight₂, . . . , Weight_(N)), wherein each weighting factorcorresponds to a different one of the circadian rhythm representativesignals received by the probability processing module 402 (i.e., eachweighting factor corresponds to a different physiological process sensedor received). Weighting factors may be used for computing theprobability indication of the occurrence of an impending disease state,such as heart failure, by providing a degree to which each physiologicalprocess's circadian rhythm enters into the probability indication. Inone example, each weight (Weight₁, Weight₂, . . . , Weight_(N)) iscomputed using historical data relating the corresponding circadianrhythm of the physiological process sensed or received to the occurrenceof impending heart failure, for example. In one such example, thehistorical data is obtained from the same subject 110 from whom thecircadian rhythm information of the physiological process is sensed orreceived. In another such example, the historical data is obtained fromat least one different subject than the circadian rhythm information(i.e., the circadian rhythm representative signal(s)) was obtained from.In a further such example, the historical data is obtained from apopulation of subjects.

Each weight may be computed using not only information about whichphysiological process the circadian rhythm is associated with, but maybe computed using information about which other or how many otherphysiological process(es)' circadian rhythms also being used to predictthe occurrence of impending heart failure or other disease state. As anillustrative example, suppose sensed or received circadian rhythms A andB each have weights of 0.1, leading to a combined prediction weight of0.2. In another example, however, the circadian rhythms A and B eachhave weights of 0.1 when these rhythms are individually used to predictthe occurrence of impending disease, but have a different (e.g., greateror lesser) weight when both are present (e.g., stronger weights of 0.5when both A and B are sufficiently present and used to predict theoccurrence of impending disease). That is, the weight values may dependon cross-correlation between two or more circadian rhythms. In a furtherexample, a weight value depends on how many circadian rhythms are beingused to compute the predicted occurrence of impending disease. As anillustrative example, suppose circadian rhythm A has a weight of 0.5when it is used alone for predicting the occurrence of impending heartfailure decompensation. In another example, however, circadian rhythm Ahas a weight of 0.25 when used in combination with one other circadianrhythm associated with a different physiological process (e.g.,circadian rhythm B or circadian rhythm C, etc.).

In one example, the prediction processing module 404 generates, usingthe probability indication output from the probability processing module402, a probability assertion or statement that an occurrence ofimpending disease will occur during a specified period after theprediction. An example of such a probability assertion or statement is a50% probability that an occurrence of impending heart failuredecompensation will occur during 5 days of the prediction generation.This assertion or statement of prediction includes both a magnitude(50%) and a well defined time period during which the prediction isapplicable (5 days).

Impending disease state prediction module 280 outputs an impendingdisease state prediction to a therapy control module 282, which in turnbases control of preventive or other therapy on the disease stateprediction. In one example, as discussed above, the impending diseasestate prediction output from the impending disease state predictionmodule 280, more particularly the prediction processing module 404,includes a set of one or more probability assertions or statements. Eachprobability statement includes both a magnitude of the probability(e.g., a 50% probability of impending heart failure decompensationexists) and a specified future time period associated therewith (e.g.,will occur within 5 days). In another example, each probabilitystatement also identifies which circadian rhythm representativesignal(s), and thus which physiological process, contributed to itsmagnitude.

In an alternative example, the impending disease state predictioncalculation and output from the impending disease state predictionmodule 280 takes the form of a conditional probability computation, suchas described in Sweeney et al., U.S. Pat. No. 6,272,377 entitled,“CARDIAC RHYTHM MANAGEMENT SYSTEM WITH ARRHYTHMIA PREDICTION ANDPREVENTION,” Girouard et al., U.S. patent application Ser. No.10/213,268 entitled, “CARDIAC RHYTHM MANAGEMENT SYSTEMS AND METHODSPREDICTING CONGESTIVE HEART FAILURE STATUS,” or Brockway et al., U.S.patent application Ser. No. 10/889,353 entitled, “EXPERT SYSTEM FORPATIENT MEDICAL INFORMATION ANALYSIS,” each of which are assigned toCardiac Pacemakers, Inc. and recite the use of conditional probabilitiesto predict the likelihood of occurrence of a future event. In thepresent context, the future event is a disease state, such as heartfailure, and the circadian rhythms sensed or received serve astriggers/markers or, more generally, the conditioning events. Theweights correlating each circadian rhythm representative signal to afuture disease state are conditional probabilities that mayalternatively be expressed as rates, as described in theabove-incorporated Sweeney et al. reference.

FIG. 5 is a block diagram illustrating one conceptual example of atherapy control module 282, which may be used to trigger one or moretherapies to a subject 110 (FIG. 1) in response to a predictedoccurrence of an impending disease state. The therapy control module 282includes an input that receives the probability assertions or statementsoutput from the impending disease state prediction module 280. In oneexample, a prediction scheduler 502 schedules the predictions ofimpending disease, such as heart failure. A therapy decision module 504decides whether therapy is warranted. The therapy selection module 506selects one or more appropriate therapies. The control module 508adjusts the selected therapy via an output to one or more of an atrialstimulation circuit 252, a ventricular stimulation circuit 256, a neuralstimulation circuit 257, a nearby external user-interface 120, or a drugpump 116, for example. The therapy control module 282 further includes atherapy list 510, which may include means to relate the therapies of thetherapy list 510 to the circadian rhythms used by the impending diseasestate prediction module 280 in predicting the occurrence of impendingheart failure, for example. The various submodules in the therapycontrol module 282 are illustrated as such for conceptual purposes only;however, these submodules may alternatively be incorporated in theimpending disease state prediction module 280 or elsewhere. As discussedbelow, such as in associated with FIG. 6, a subject's 110 (FIG. 1)response to the applied therapy may be monitored via the subject'spost-therapy circadian rhythms.

In one example, the therapy selection module 506 selects a heart failurepreventive therapy using outputs from the therapy decision module 504.If the therapy decision module 504 determines that the degree andconfidence in the impending disease state prediction warrants sometherapy, then the therapy selection module 506 selects a member of thetherapy list 510 to be invoked. In another example, the therapy sectionmodule 506 selects a therapy that is only secondarily related to thepredicted disease state.

In another example, the therapy list 510 includes all possible diseasestate preventive therapies or secondarily related therapies that system100 (FIG. 1) may deliver or communicate to the subject 110. The therapylist 510 may be programmed into the IMD 102 either in hardware,firmware, or software. In yet another example, the therapy list 510includes immediate, short-term, intermediate-term, or long-term heartfailure preventive therapies. Immediate heart failure preventivetherapies include, by way of example, initiating or changing a drugtherapy administered to a subject 110 via an implantable drug pump 116or electrical stimulation administered to the subject 110 via one ormore electrode bearing leads 108. Short-term heart failure preventivetherapies include, by way of example, administering a continuouspositive air pressure (“CPAP”) dose to the subject 110 or notifying acaregiver to initiate or change the subject's drug treatment program.Intermediate-term heart failure preventive therapies include, by way ofexample, adjusting the subject's 110 (FIG. 1) lifestyle (e.g., decreasesalt or water consumption). Finally, long-term heart failure preventivetherapies include, by way of example, notifying the subject 110 orcaregiver to alter the drug which takes longer to affect the subject(e.g., beta blockers, ACE inhibitors) or administering CRT to thesubject.

Each member of the therapy list 510 may be associated with a requiredtime of action, which includes one or more of a time for the therapy tobecome effective or a time after which the therapy is no longereffective. Accordingly, in one example, the prediction scheduler 502considers only those members of the therapy list 510 that can beexpected to be effective within a time frame commensurate with theprediction time period. In another example, only one member of thetherapy list 510 is invoked at any particular time. In a furtherexample, combinations of different therapies are provided atsubstantially the same time.

FIG. 6 is a block diagram illustrating exemplary physiological processesof a subject 110 (FIG. 1) having circadian rhythms, which when lost orchanged from a baseline, may be associated with an occurrence ofimpending heart failure or other disease state. In varying examples, oneor more of the circadian rhythms associated with the physiologicalprocesses 602-628 are used to predict, monitor, or treat an occurrenceof impending heart failure in the subject 110. In certain examples, timedetectors, such as a time of the circadian rhythm representative signalssensed or received, an arrhythmia incidence, or a clinical event, areused additionally or alternatively to predict, monitor, or treat theoccurrence of impending heart failure. While the following discussesexemplary physiological processes 602-628 having circadian rhythms whosepresence, absence, or baseline change is statistically associated withan occurrence of impending heart failure, the list is not meant to beexhaustive, and may include other processes 622 not herein discussed.

In one example, the subject's peripheral or core body temperature 602 isused as a physiological process having a certain circadian rhythm, whichwhen lost or changed from a baseline, may be associated with impendingheart failure. In healthy subjects, the human body temperature follows adefinite circadian rhythm. For instance, in the late afternoon, ahealthy subject's body temperature can be as much as 2° F. higher thanin the morning. This circadian rhythm, however, may begin to become lesspronounced or otherwise change several hours to several days before theonset of a disease state, such as heart failure. Monitoring thecircadian rhythm associated with body temperature in such instances andcomparing the results to one or more baseline prediction criteriaderived from one or more subjects in a non-disease state, provides atool to predict, monitor, or treat an occurrence of impending heartfailure. In one example, the circadian rhythm associated with thesubject's body temperature is measured by a temperature sensor 260 (FIG.2), such as a temperature capsule embedded under the skin.

In another example, the subject's heart rate or heart rate variability(“HRV”) 604 is used as a physiological process having a certaincircadian rhythm, which when lost or changed from a baseline, may beassociated with impending heart failure. In healthy subjects having HRV,the heart rate intervals have a circadian rhythm, with HRV generallyincreasing during periods of sleep. This circadian rhythm, however, maybecome less pronounced, more irregular, or otherwise change severalhours to several days before the onset of a disease state, such as heartfailure. Monitoring HRV in such instances and comparing the variabilityto one or more baseline prediction criteria derived from one or moresubjects in a non-disease state, provides a tool to predict, monitor, ortreat an occurrence of impending heart failure. In one example, thecircadian rhythm associated with HRV is determined by standarddeviation, variance, or other characteristic indicative of variability.In another example, the circadian rhythm associated with HRV is measuredby a heart rate/heart rate variability sensor 266 (FIG. 2).

In a similar manner, the subject's heart rate may also be used in theprediction of impending heart failure. In healthy subjects, the heartrate follows a certain circadian rhythm. For instance, a healthysubject's heart rate is typically lower during the sleep hours thanduring the awake hours. This circadian rhythm, however, may become lostor change from a baseline several hours to several days before the onsetof a disease state, such as heart failure. In many instances, heart rate604 during sleep may actually increase before the onset of the diseasestate and lower frequency components of HRV 604 associated with abnormalsympathetic activation may also increase.

In another example, the subject's blood pressure 606 is used as aphysiological process having a certain circadian rhythm, which when lostor changed from a baseline, may be associated with impending heartfailure. In healthy subjects, blood pressure follows a circadian rhythm.For instance, the blood pressure typically rises in the morning andstays elevated until late afternoon, at which time it drops off and hitsits lowest point during the night. This circadian rhythm, however, maybegin to become less pronounced or otherwise change several hours toseveral days before the onset of a disease state, such as heart failure.Monitoring the circadian rhythm associated with blood pressure in suchinstances and comparing the results to one or more baseline predictioncriteria derived from one or more subjects in a non-disease state,provides a tool to predict, monitor, or treat an occurrence of impendingheart failure. In one example, the circadian rhythm associated with thesubject's blood pressure is measured by a blood pressure sensor 258(FIG. 2).

In another example, the subject's respiratory rate or respiratory ratevariability (“RRV”) 608 is used as a physiological process having acertain circadian rhythm, which when lost or changed from a baseline,may be associated with impending heart failure. In healthy subjects, therespiratory rate variability follows a circadian rhythm. This circadianrhythm, however, may become lost or change from a baseline several hoursto several days before the onset of a disease state, such as heartfailure. Indications of a loss or baseline change of circadian rhythmmay include a low frequency component of the subject's respiratory ratedecreasing (as the subject is less likely to be active), and a highfrequency component increasing. Monitoring respiratory rate in suchinstances and comparing the variability to one or more baselineprediction criteria derived from one or more subjects in a non-diseasestate, provides a tool to predict, monitor, or treat an occurrence ofimpending heart failure. In one example, the circadian rhythm associatedwith RRV is measured by a respiratory rate sensor 262 (FIG. 2). In onesuch example, the respiratory rate sensor 262 includes an implantablebreathing rate module which includes a fiducial point detector adaptedto detect a fiducial point on the breathing signal that occurs a knownnumber of one or more times during the breathing cycle and a timermeasuring the time interval between respective successive fiducialpoints. In another such example, the respiratory rate sensor 262includes an implantable transthoracic impedance sensor to peak-detect,level-detect, or otherwise detect impedance variations resulting frombreathing, such as is described in Dalal et al., U.S. patent applicationSer. No. 11/458,602 entitled, “SLEEP STATE DETECTION,” which is assignedto Cardiac Pacemakers, Inc.

In another example, the subject's tidal volume or minute ventilation(“MV”) 610 is used as a physiological process having a certain circadianrhythm, which when lost or changed from a baseline, may be associatedwith impending heart failure. In healthy subjects, tidal volume and MVfollow a circadian rhythm. For instance, when plotted on a number ofevents vs. MV counts histogram graph, an upper portion of a MV histogramrepresents daytime MV, while a lower portion represents nighttime MV.This circadian rhythm, however, may begin to become less pronounced orotherwise change several hours to several days before the onset of adisease state, such as heart failure. Monitoring the circadian rhythmassociated with tidal volume or minute ventilation in such instances andcomparing the results to one or more baseline prediction criteriaderived from one or more subjects in a non-disease state, provides atool to predict, monitor, or treat an occurrence of impending heartfailure. In one example, the circadian rhythm associated with thesubject's tidal volume or minute ventilation is measured by an internalsensor 262 (FIG. 2), such as a rate detector and an impedance sensor.

In another example, the subject's activity level 612 is used as aphysiological process having a certain circadian rhythm, which when lostor changed from a baseline, may be associated with impending heartfailure. In healthy subjects, activity level follows a circadian rhythm.This circadian rhythm, however, may begin to become less pronounced orotherwise change several hours to several days before the onset of adisease state, such as heart failure. Indications of a loss or baselinechange of circadian rhythm may include a decrease in the subject'sactivity level. Monitoring the circadian rhythm associated with activitylevel in such instances and comparing the results to one or morebaseline prediction criteria derived from one or more subjects in anon-disease state, provides a tool to predict, monitor, or treat anoccurrence of impending heart failure. In one example, the circadianrhythm associated with the subject's activity level is measured by anactivity level sensor 270 (FIG. 2). In another example, the circadianrhythm associated with the subject's activity level is measured using,at least in part, an indication of activity level input into a nearbyexternal user interface 120 (FIG. 2) by the subject.

In another example, the subject's posture 614 is used as a physiologicalprocess having a certain circadian rhythm, which when lost or changedfrom a baseline, may be associated with impending heart failure. Inhealthy subjects, posture follows a circadian rhythm. This circadianrhythm, however, may begin to become less pronounced, more irregular, orotherwise change several hours to several days before the onset of adisease state, such as heart failure. Indications of a loss or baselinechange of circadian rhythm may include the subject's increasingly supineposture orientation. Monitoring the circadian rhythm associated withposture in such instances and comparing the results to one or morebaseline prediction criteria derived from one or more subjects in anon-disease state, provides a tool to predict, monitor, or treat anoccurrence of impending heart failure. In one example, the circadianrhythm associated with the subject's posture is measured by a posturesensor 268 (FIG. 2), such as a two-axis accelerometer having Model No.ADXL202E, manufactured by Analog Device, Inc. of Norwood, Mass., U.S.A.In another example, the subject's posture is measured using techniquesdescribed in Hatlestad et al., U.S. patent application Ser. No.10/267,982, entitled “DETECTION OF CONGESTION FROM MONITORING PATIENTRESPONSE TO RECUMBENT POSITION,” which is also assigned to CardiacPacemakers, Inc.

In another example, the pattern of the subject's wake/sleep cycle 618 isused as a physiological process having a certain circadian rhythm, whichwhen lost or changed from a baseline, may be associated with impendingheart failure. In healthy subjects, sleep patterns follow an organizedcircadian rhythm. For instance, one is most likely to sleep soundly whenhis/her temperature is lowest, in the early morning hours, and mostlikely to awaken when his/her temperature starts to rise around6:00-8:00 am. This circadian rhythm, however, may begin to become lessorganized several hours to several days before the onset of a diseasestate, such as heart failure. Monitoring the circadian rhythm associatedwith sleep patterns 618 in such instances and comparing the results toone or more baseline prediction criteria derived from one or moresubjects in a non-disease state, provides a tool to predict, monitor, ortreat an occurrence of impending heart failure.

The circadian rhythm associated with the subject's wake/sleep cycle 618may be measured by an internal sleep detector 272 (FIG. 2), which insome examples determines both the amount of quality of the subject'ssleep. One example of a sleep detector is described in Carlson et al.,U.S. patent application Ser. No. 09/802,316 entitled, “CARDIAC RHYTHMMANAGEMENT SYSTEM USING TIME-DOMAIN HEART RATE VARIABILITY INDICIA,”which is assigned to Cardiac Pacemakers, Inc. Another example of a sleepdetector is described in Dalal et al., U.S. patent application Ser. No.11/458,602 entitled, “SLEEP STATE DETECTION,” which is assigned toCardiac Pacemakers, Inc. Yet another example of a sleep detector isdescribed in Ni et al., U.S. patent application Ser. No. 10/309,771entitled, “SLEEP DETECTION USING AN ADJUSTABLE THRESHOLD,” which isassigned to Cardiac Pacemakers, Inc. Alternatively, the subject 110 orcaregiver may enter an indication of his/her sleep quality or durationinto an external user interface 120 or 122 (FIG. 2).

In another example, the subject's thoracic impedance 624 is used as aphysiological process having a certain circadian rhythm, which when lostor changed from a baseline, may be associated with impending heartfailure. In healthy subjects, thoracic impedance 624 follows a circadianrhythm in which impedance is lower during the night and early morninghours and higher during the mid-to-date afternoon. This circadianrhythm, however, may begin to shift, become less pronounced, orotherwise change several hours to several days before the onset of adisease state, such as heart failure. Monitoring the circadian rhythmassociated with thoracic impedance 624 and comparing the results to oneor more baseline prediction criteria derived from one or more subjectsin a non-disease state, provides a tool to predict, monitor, or treat anoccurrence of impending heart failure. In one example, the circadianrhythm associated with the subject's thoracic impedance 624 is measuredby injecting an electrical stimulus current of known or attainable value(e.g., via the ventricular 256 or atrial 252 stimulation circuits) toone or more implanted electrodes and measuring (e.g., via theventricular 254 or atrial 250 sense circuits) the resulting voltageusing one or more other implanted electrodes. Using information aboutthe current and the resulting voltage, the IMD 102 may calculate animpedance by taking a ratio of resulting voltage to injected current.

In yet another example, the subject's heart sounds 628 (for example,heart sounds referred to in the art as S₁, S₂, and particularly theheart sound referred to in the art as S₃) are used as a physiologicalprocess having a certain circadian rhythm, which when lost or changedfrom a baseline, may be associated with impending heart failure. Inhealthy subjects, heart sounds 628 follow a circadian rhythm. Thiscircadian rhythm, however, may begin to become less pronounced, changefrequency, or otherwise change several hours to several days before theonset of a disease state, such as heart failure. In one example, thecircadian rhythm associated with the subject's heart sounds 628 ismeasured by an implantable accelerometer, microphone or otherimplantable sensor, such as by using the systems and methods describedby Lincoln et al., U.S. Pat. No. 6,665,564 entitled, “CARDIAC RHYTHMMANAGEMENT SYSTEM SELECTING A-V DELAY BASED ON INTERVAL BETWEEN ATRIALDEPOLARIZATION AND MITRAL VALVE CLOSURE,” or the systems and methodsdescribed in Lincoln et al., U.S. patent application Ser. No. 10/099,865entitled, “CARDIAC RHYTHM MANAGEMENT SYSTEM AND METHOD USING TIMEBETWEEN MITRAL VALVE CLOSURE AND AORTIC EJECTION,” each of which isassigned to Cardiac Pacemakers, Inc. In another example, the heartsounds 628 are measured by a caregiver while the subject is lying onhis/her side, and a numerical value indicative of a heart soundfrequency of amplitude is input into an external user interface 120, 122(FIG. 2), by the caregiver.

Alternatively or additionally, a time of the circadian rhythmrepresentative signals sensed or received, an arrhythmia incidence, or aclinical event may be used to predict, monitor, or treat an occurrenceof impending disease. As one example, the time of a subject's clinicalevent is entered into an external user-interface 120, 122 and used topredict, monitor, or treat the occurrence of impending disease.Admissions to the emergency room for pulmonary edema not associated withacute myocardial infarction is highest between 8:00 am-Noon and 8:00pm-12:00 am and lowest between Noon-8:00 pm. Thus, clinical admission incombination with a reduced body temperature 602 in the late afternoon,for instance, may indicate the onset of a disease state, such as heartfailure.

As another example, the time of a subject's arrhythmia or abnormalbreathing incidence (e.g., apnea, hypopnoea, or periodic breathing) isused to predict, monitor, or treat the occurrence of impending disease.A cardiac arrhythmia incidence is any disorder of the heart rate orrhythm. The presence of one or more cardiac arrhythmias may correlate toan occurrence of impending heart failure. In one example, as discussedabove, the IMD 102 (FIG. 2) may utilize an atrial 252 (FIG. 2) andventricular 254 (FIG. 2) sensing circuit to sense cardiac signals fordetermining whether a rhythm is normal or pathologic. In anotherexample, the subject or caregiver enters a detected presence of one ormore cardiac arrhythmia, found using an echocardiogram or other imaginginstrument, into an external user interface 120 or 122 (FIG. 2).

FIGS. 7A-7C illustrate exemplary graphs that may be generated by system100 and which illustrate circadian rhythm comparisons that may be madebetween circadian rhythms associated with at least one physiologicalprocess sensed or received and one or more baseline circadian rhythmprediction criteria. These illustrations, when displayed on an externaluser interface 120, 122 display screen (FIG. 1), for example, may beused by a subject 110 (FIG. 1) or caregiver to predict, monitor, ortreat an occurrence of impending heart failure or other disease state.

FIG. 7A illustrates circadian rhythms associated with respiration rate608 (FIG. 6) plotted on a respiration rate (breaths/minute) vs. time(hours) graph. As shown, the respiration circadian rhythm of a healthysubject 700 includes a pronounced, regular pattern; whereas, therespiration circadian rhythm of an unhealthy subject 702 includes a lesspronounced and irregular pattern. More specifically, the unhealthysubject has a higher maximum respiratory rate, a higher mean/medianrespiratory rate, and less variability in minimum/mean/medianrespiratory rate in comparison to the healthy subject. Since therespiration circadian rhythm of the unhealthy subject 702 is lost orchanged relative to the healthy subject's baseline circadian rhythm 700,a prediction of impending disease, such as heart failure, may have beenin order for the unhealthy subject as soon as such loss or change can bemade with a reasonable degree of certainty.

FIG. 7B illustrates an alternative way to graphically illustratecircadian rhythms associated with respiration rate 608 (FIG. 6) of ahealthy and unhealthy subject. In FIG. 7B, conceptualized (i.e., notreal) data of the daily variability of the respiratory rate is plottedagainst the daily median of the respiratory rate. In thisconceptualization, the healthy subject 700 maintains a lower medianrespiratory rate and higher variability in the mean respiratory ratethan the unhealthy subject 702. Among other things, such characteristicsof the healthy subject may indicate an easier time breathing and agreater activity level than the unhealthy subject.

FIG. 7C illustrates a circadian rhythm associated with a subject'swake/sleep cycle 618 (FIG. 6). Initially, on days 1-3, the subjectfollows a substantially regular sleep schedule, including sleeping fromabout 12:00-5:00 am each day. Such regular sleep schedule is indicativeof a healthy subject 700. In contrast, on days 4-8, the subject followsa very irregular sleep schedule. For instance, on day 4, the subjectsleeps from about 12:00-1:00 am and 4:30-5:30 am. Then, on day 5, thesubject sleeps from about 9:00 pm-12:00 am, 1:00-4:30 am, and from5:30-6:00 am. Such irregular sleep schedule is indicative of a unhealthysubject 702.

Subjects with severe heart failure often suffer from inability to sleepeither due to pulmonary congestion or inability to tolerate a supineposture. In addition, evidence from sleep studies indicate that as aperson nears death, the time in which the subject sleeps becomes muchmore fragmented. By visually seeing the sleep regularity (orirregularity, as it may be), caregivers (or the subject themselves) maybe able to determine if the subject's health state is changing due to apossible worsening in disease state. Since the sleep circadian rhythm ofthe unhealthy subject 702 is lost or changed relative to the healthysubject's baseline circadian rhythm 700, a prediction of impendingdisease, such as heart failure, may have been in order for the unhealthysubject as soon as such loss (marked by irregularity) could be made witha reasonable degree of certainty.

FIG. 8 illustrates one example of a method 800 of predicting,monitoring, or treating an occurrence of impending disease, such asheart failure, in a subject. At 802, one or more baseline circadianrhythm prediction criteria are stored. This may be accomplished in anumber of ways. In one example, the one or more baseline circadianrhythm prediction criteria are loaded into an IMD before, during, orafter the IMD is implanted in the subject. The one or more baselinecircadian rhythm prediction criteria may be established in a number ofways. In one example, the one or more baseline circadian rhythmprediction criteria are derived using one or more past physiologicalprocess observation of the subject when in a non-disease health state.In another example, the one or more baseline circadian rhythm predictioncriteria are derived using one or more past physiological processobservation of a population in a non-disease health state.

At 804, at least one physiological process having a circadian rhythmwhose presence, absence, or baseline change is statistically associatedwith a disease state, is sensed or received. This may be accomplished ina number of ways. In one example, the at least one physiological processhaving the circadian rhythm is sensed or received via a physiologicalinformation collection device. The circadian rhythm representativesignals sensed or received may be associated with various physiologicalprocesses, such as body temperature (core or peripheral), heart rate,heart rate variability, respiration rate, respiration rate variability,minute ventilation, activity, blood pressure, posture, tidal volume,sleep quality or duration, thoracic impedance, or heart sounds.

At 806, the circadian rhythm associated with the at least onephysiological process sensed or received is compared with the one ormore baseline circadian rhythm prediction criteria. This may beaccomplished in a number of ways. In one example, a probabilitycomparator of an impending disease state prediction module compares oneor more sensed or received circadian rhythm representative signal (S₁,S₂, . . . , S_(N)) values to corresponding baseline circadian rhythmprediction criteria (C₁, C₂, . . . , C_(N)) values. When the values ofthe circadian rhythm representative signals sensed or received differ bymore than a specified amount from the baseline circadian rhythmprediction criteria, thereby indicating a loss or baseline change ofcircadian rhythm, a positive probability indication of the occurrence ofimpending heart failure results at 808. When the values of the circadianrhythm representative signals sensed or received are substantiallysimilar to the baseline circadian rhythm prediction criteria, thereforeindicating no substantial loss or baseline change of circadian rhythm, anegative probability indication of the occurrence of impending heartfailure results at 810 and the process returns to 804.

Optionally, at 812, each circadian rhythm representative signal (S₁, S₂,. . . , S_(N)) value differing from the corresponding baseline circadianrhythm prediction criteria (C₁, C₂, . . . , C_(N)) value by more thanthe specified amount is weighted. This may be accomplished in a numberof ways. In one example, for each circadian rhythm representative signal(S₁, S₂, . . . , S_(N)) value differing from the corresponding baselinecircadian rhythm prediction criteria (C₁, C₂, . . . , C_(N)) value bymore than the specified amount, a weighting module of the impendingdisease state prediction module stores weighting factors (Weight₁,Weight₂, . . . , Weight_(N)). In another example, each weighting factor(Weight₁, Weight₂, . . . , Weight_(N)) provides a degree to which eachcircadian rhythm representative signal differing from the correspondingbaseline circadian rhythm prediction criteria by more than the specifiedamount enters into a probability indication computed at 814. In yetanother example, each weight is computed using not only informationabout which physiological process the circadian rhythm relates to, butalso using information about which other physiological processes havingcircadian rhythms are also being used to predict the occurrence ofimpending heart failure.

At 816, a probability assertion or statement of impending heart failureis made. This may be accomplished in a number of ways. In one example, aprediction processing module of the impending disease state predictionmodule generates, using the probability indication output, a probabilityassertion or statement that a heart failure will occur (e.g., within aspecified time period after the prediction). In another example, atleast one of the sensing or receiving, comparing, or predicting isperformed, at least in part, implantably.

At 818, an alert of the predicted occurrence of impending heart failuredecompensation is provided to the subject or a caregiver. The alert maybe communicated in a number of ways. In one example, an audible tone issounded. In another example, the subject is linked up to a remotemonitoring system (e.g., via a communication repeater) thereby allowingthe alert to be electronically communicated to the caregiver for review.In yet another example, muscle tissue in the locality of the IMD withinthe subject is stimulated. In a further example, the alert includestransmitting information about the predicted occurrence of impendingheart failure and information used to make the prediction to an externaluser interface. In this way, the information used to make the predictionmay be presented to the subject or caregiver on the interface's LCD orother display.

At 820, one or more appropriate therapies are selected (e.g., drugtherapy or neurostimulation). In one example, one or more heart failurepreventive therapy is selected. In another example, one or more therapysecondarily related to heart failure is selected. The therapy selectionmay be accomplished in a number of ways. In one example, a therapyselection module selects the one or more appropriate preventive or othertherapies. At 822, a therapy is initiated using the predicted occurrenceof impending heart failure (e.g., within a specified prediction timeperiod). This may be accomplished in a number of ways. In one example,an control module activates the selected therapy via an output to a anatrial stimulation circuit, a ventricular stimulation circuit, a neuralstimulation circuit, or a drug pump.

By monitoring post-therapy circadian rhythms, the efficacy and necessaryamount of therapy may be determined. To this end, at least onephysiological process having a circadian rhythm, whose presence,absence, or baseline change is statistically associated with a diseasestate, is sensed or received at 824. This may be accomplished in anumber of ways, such as those discussed in regard to the method at 804.At 826, the circadian rhythm associated with the at least onephysiological process sensed or received is compared with the one ormore baseline circadian rhythm prediction criteria, such as at 806. Whenthe values of the circadian rhythm representative signals sensed orreceived differ by more than a specified amount from the baselinecircadian rhythm prediction criteria, an increase in the amount ofselected therapy may be warranted at 828. When the values of thecircadian rhythm representative signals sensed or received aresubstantially similar to the baseline circadian rhythm predictioncriteria, a titration of the selected therapy may be warranted at 828;additionally, if applicable, a discharge of the subject from thehospital may be reasonable at 830.

CONCLUSION

Heart failure is a common clinical entity, particularly among theelderly, but is often not treated (if at all) until the disease isdetected late in the disease process via associated physical symptoms,such as abnormal thoracic fluid build-up behind the heart.Advantageously, the present systems and methods allow for theprediction, monitoring, or treatment of impending heart failure or otherdisease states by monitoring one or more circadian rhythms associatedwith a subject's physiological process. Practically every physiologicalprocess in the human body exhibits circadian rhythmicity, and thus, themonitoring of circadian rhythm provides an adequate means forpredicting, monitoring, or treating an impending disease state, such asheart failure or heart failure decompensation, among others.

The time savings provided by prediction (as opposed to detection alone),may reduce or eliminate expensive hospitalization and aid in avoiding adecompensation crisis or properly managing a heart failure subject, forexample, in a state of relative well-being. Further, the present systemsand methods provide an alert to the subject or the subject's caregiverregarding a positive prediction of impending heart failure or otherdisease state. Further yet, the present systems and methods may adjust(or initiate) a therapy (e.g., drug therapy or neurostimulation) toprevent or minimize impending disease state using the prediction andmonitor the efficacy of such therapy (including monitoring the subject'srecovery).

While the present systems and methods may be used to monitor processrhythms on a variety of cycle periods, such as circadian, circaseptan,circatrigintan, circannual, holidays, weekdays, weekends, or menstrual,collectively “chronobiological rhythms”, a majority of the foregoingdescription is cast in terms of circadian rhythm monitoring forexemplary purposes. Such description is not intended, however, to limitthe scope of the present subject matter in any way. Furthermore, a lossor baseline change of chronobiological (e.g., circadian) rhythm maysignify an occurrence of an impending disease state other than justheart failure. For instance, a breakdown in chronobiological rhythm mayoccur during general sickness (e.g., a flu or cold), neurological,mental or pulmonary disease, a viral or bacterial infection, othercardiovascular diseases (e.g., diabetes) or even cancer. As such, thispatent document is intended to be commensurate in scope to cover theseadditional embodiments.

It is to be understood that the above description is intended to beillustrative, and not restrictive. For example, the above-describedembodiments (or aspects thereof) may be used in combination with eachother. Many other embodiments will be apparent to those of skill in theart upon reviewing the above description. The scope of the presentsystems and methods should therefore, be determined with reference tothe appended claims, along with the full scope of legal equivalents towhich such claims are entitled. In the appended claims, the term“including” is used as the plain-English equivalents of the respectiveterms “comprising” and “wherein.” Also, in the following claims, theterms “including” and “comprising” are open-ended, that is, a system,device, article, or process that includes elements in addition to thoselisted after such a term in a claim are still deemed to fall within thescope of that claim. Moreover, in the following claims, the terms“first,” “second,” and “third,” etc. are used merely as labels, and arenot intended to impose numerical requirements on their objects.

The Abstract of the Disclosure is provided to comply with 37 C.F.R.§1.72(b), requiring an abstract that will allow the reader to quicklyascertain the nature of the technical disclosure. It is submitted withthe understanding that it will not be used to interpret or limit thescope or meaning of the claims. In addition, in the foregoing DetailedDescription, various features may be grouped together to streamline thedisclosure. This method of disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter may lie in less thanall features of a single disclosed embodiment. Thus the following claimsare hereby incorporated into the Detailed Description, with each claimstanding on its own as a separate embodiment.

1. A system comprising: a prediction criteria module, adapted to storeinformation about one or more chronobiological rhythm predictioncriteria; a physiological information collection device, adapted tosense or receive information about at least one physiological processhaving a chronobiological rhythm whose presence, absence, or change isstatistically associated with a disease state; an impending diseasestate prediction module, coupled to the prediction criteria module toreceive the one or more chronobiological rhythm prediction criteria andcoupled to the physiological information collection device to receivethe chronobiological rhythm of the at least one physiological process,the impending disease state prediction module being adapted to predictan occurrence of impending disease using the one or morechronobiological rhythm prediction criteria and the chronobiologicalrhythm of the at least one physiological process; and at least one ofthe prediction criteria module, the physiological information collectiondevice, or the impending disease state prediction module including animplantable portion.
 2. The system of claim 1, wherein the impendingdisease state prediction module is adapted to predict the occurrence ofimpending disease during a specified prediction time period.
 3. Thesystem of claim 1, wherein the information about the at least onephysiological process is sensed or received, at least in part, using animplantable device or sensor.
 4. The system of claim 1, wherein the atleast one physiological process includes one or more of bodytemperature, heart rate, heart rate variability, respiration rate,respiration rate variability, minute ventilation, tidal volume,activity, blood pressure, posture, sleep pattern, thoracic impedance, orat least one heart sound.
 5. The system of claim 4, further comprising atiming circuit coupled to the physiological information collectiondevice to provide an associated collection time to the chronobiologicalrhythm of the at least one physiological process; and wherein theassociated collection time is used by the impending disease stateprediction module to predict the occurrence of impending disease.
 6. Thesystem of claim 1, further comprising an arrhythmia detector adapted tosense or receive information about an arrhythmia incidence; and whereina time of the arrhythmia incidence is used by the impending diseasestate prediction module to predict the occurrence of impending disease.7. The system of claim 1, wherein the predicted occurrence of impendingdisease is computed using one or more stored weighting factor, eachweighting factor corresponding to a chronobiological rhythm of adifferent one of the at least one physiological process.
 8. The systemof claim 1, wherein the chronobiological rhythm prediction criteria arederived using one or more past physiological process observation from asubject in a non-disease state.
 9. The system of claim 1, furthercomprising a therapy control module adapted to adjust or initiate atherapy using the predicted occurrence of impending disease.
 10. Thesystem of claim 9, further comprising an implantable drug pump, coupledto the therapy control module to receive one or more drug deliveryinstruction.
 11. The system of claim 9, further comprising a neuralstimulation circuit, coupled to the therapy control module to receiveone or more neurostimulation delivery instruction.
 12. The system ofclaim 9, further comprising at least one of a ventricular or atrialstimulation circuit, coupled to the therapy control module to receiveone or more cardiac stimulation delivery instruction.
 13. A methodcomprising: sensing or receiving at an implantable device, informationabout at least one physiological process having a chronobiologicalrhythm whose presence, absence, or change is statistically associatedwith a disease; comparing the chronobiological rhythm of the at leastone physiological process to one or more chronobiological rhythmprediction criteria; and at least one of predicting, detecting, oridentifying an occurrence of disease using the comparison.
 14. Themethod of claim 13, wherein predicting the occurrence of diseaseincludes predicting an occurrence of impending disease occurring duringa specified prediction time period.
 15. The method of claim 13, whereinsensing or receiving the information about the at least onephysiological process includes sensing or receiving at least one of bodytemperature, heart rate, heart rate variability, respiration rate,respiration rate variability, minute ventilation, tidal volume,activity, blood pressure, posture, sleep pattern, thoracic impedance, orat least one heart sound.
 16. The method of claim 13, further comprisingsensing or receiving information about at least one arrhythmiaincidence; and wherein predicting the occurrence of disease includesusing a time of day of the arrhythmia incidence.
 17. The method of claim13, further comprising adjusting or initiating a therapy using thepredicted, detected, or identified occurrence of disease.
 18. The methodof claim 17, wherein adjusting or initiating the therapy includesdetermining a drug delivery time using the chronobiological rhythm ofthe at least one physiological process.
 19. The method of claim 17,wherein adjusting or initiating the therapy includes recovering thechronobiological rhythm of the at least one physiological process usingone or both of drug delivery or neurostimulation.
 20. The method ofclaim 17, further comprising monitoring the efficacy of the therapyusing a post-therapy chronobiological rhythm of the at least onephysiological process.
 21. A method comprising: sensing or receiving atan implantable device, information about at least one physiologicalprocess having a chronobiological rhythm whose presence, absence, orchange is statistically associated with a disease; comparing thechronobiological rhythm of the at least one physiological process to oneor more chronobiological rhythm prediction criteria; and applying atherapy.
 22. The method of claim 21, wherein applying the therapyincludes using the comparison of the chronobiological rhythm and the oneor more chronobiological rhythm prediction criteria.
 23. The method ofclaim 21, wherein applying the therapy includes using asubject-responsive drug delivery time derived using one or more pastpost-therapy chronobiological rhythm observations from a subject in asimilar pre-therapy disease-state.
 24. The method of claim 21, furthercomprising monitoring the efficacy of the therapy using a post-therapychronobiological rhythm of the at least one physiological process. 25.The method of claim 21, wherein sensing or receiving the informationabout the at least one physiological process includes sensing orreceiving at least one of body temperature, heart rate, heart ratevariability, respiration rate, respiration rate variability, minuteventilation, tidal volume, activity, blood pressure, posture, sleeppattern, thoracic impedance, or at least one heart sound.
 26. A methodcomprising: applying a therapy to a subject; and monitoring the efficacyof the therapy, including sensing or receiving at an implantable devicea post-therapy chronobiological rhythm associated with at least one ofbody temperature, heart rate, heart rate variability, respiration rate,respiration rate variability, minute ventilation, tidal volume,activity, blood pressure, posture, sleep pattern, thoracic impedance, orat least one heart sound.
 27. The method of claim 26, wherein applyingthe therapy includes delivering one or both of drug or electricalstimulation therapy to the subject.
 28. The method of claim 26, furthercomprising titrating the therapy using the monitored efficacy of thetherapy.